Derrick Hang February 24, 2010 Economics 201FS

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Presentation transcript:

Derrick Hang February 24, 2010 Economics 201FS Data Analysis II Derrick Hang February 24, 2010 Economics 201FS

Corrections: The Data Apple Inc. (AAPL): April 16, 1997 – January 7, 2009 2,920 Days IBM (IBM): April 9, 1997 – January 7, 2009 2,925 Days Proctor Gamble Co (PG): 2,924 Days * *Absence of a day from PG was found to be on March 7, 2000; this is when PG released a warning that earnings for the rest of the fiscal year will fall short of expectations, contributing 142 to the 374 point drop in the Dow that day

Modifications 8 minute intervals are used so the intervals fit exactly with the 385 minutes per day window; in other words, there is no incomplete interval left over at the end of each day i.e. to obtain the first 8-minute return you take the price level at the 1st min. and the 9th min., then the 9th and the 15th, etc.; following this sequence, we end up using the price level at the 385th and 377th min. 8 minute is consistent with the volatility signature plots presented last time, and leaves no incomplete interval at the end

Returns for 8-minute intervals

Corrected MA TP Jump test

Corrected MA TP Jump test IBM 0.1% Significance Level = 75 / 2925 (2.56%) 1% Significance Level = 219 / 2925 (7.49%) 5% Significance Level = 539 / 2925 (18.43%) PG 0.1% Significance Level = 82 / 2924 (2.80%) 1% Significance Level = 223 / 2924 (7.63%) 5% Significance Level = 548 / 2924 (18.74%) AAPL 0.1% Significance Level = 113 / 2920 (3.87%) 1% Significance Level = 305 / 2920 (10.45%) 5% Significance Level = 625 / 2920 (21.40%)

Corrected MA QP Jump test

Corrected MA QP Jump test IBM 0.1% Significance Level = 80 / 2925 (2.74%) 1% Significance Level = 236 / 2925 (8.07%) 5% Significance Level = 559 / 2925 (19.11%) PG 0.1% Significance Level = 94 / 2924 (3.21%) 1% Significance Level = 238 / 2924 (8.14%) 5% Significance Level = 563 / 2924 (19.25%) AAPL 0.1% Significance Level = 136 / 2920 (4.66%) 1% Significance Level = 326 / 2920 (11.16%) 5% Significance Level = 653 / 2920 (22.36%)

AAPL Jump Detection: Median Test 0.1% Significance Level = 65 / 2920 (2.23%) 1% Significance Level = 143 / 2920 (4.90%) 5% Significance Level = 328 / 2920 (11.23%)

IBM Jump Detection: Median Test 0.1% Significance Level = 57 / 2925 (1.95%) 1% Significance Level = 126 / 2925 (4.31%) 5% Significance Level = 278 / 2925 (9.50%)

PG Jump Detection: Median Test 0.1% Significance Level = 61 / 2924 (2.09%) 1% Significance Level = 143 / 2924 (4.89%) 5% Significance Level = 285 / 2924 (9.75%)

Exploring topics: Forecasting Bayesian Forecasting with Dynamic Models using high-frequency data Regression where every variable varies with time Better coefficients from use of high frequency data? What time window has better predictability? What should be the dependent: returns, prices, volatility?